Chiara Campagnola
About Chiara Campagnola
Chiara Campagnola is a Machine Learning Engineer currently working at Carbon Re in London, England. She holds an MSc in Machine Learning from UCL and has previous experience as an instructor and software engineering intern.
Current Role at Carbon Re
Chiara Campagnola serves as a Machine Learning Engineer at Carbon Re since 2021. In this role, she focuses on developing machine learning models that enhance real-time intelligence and monitoring capabilities. Her work contributes to improving the reliability of systems within the organization. Carbon Re is known for its commitment to leveraging technology for environmental sustainability.
Previous Experience at Fire Tech Camp
In 2017, Chiara Campagnola worked as an Instructor at Fire Tech Camp in London, UK, for a duration of one month. During her time there, she engaged with students to teach foundational concepts in technology and coding, fostering interest in STEM fields among young learners.
Internship at Capital One
Chiara Campagnola completed a Software Engineering Internship at Capital One in 2018. This internship lasted for two months and provided her with practical experience in software development within the financial sector, allowing her to apply her academic knowledge in a professional environment.
Educational Background at UCL
Chiara Campagnola pursued her Master of Science in Machine Learning at University College London (UCL) from 2019 to 2021. Prior to that, she earned a Bachelor of Engineering in Electronic and Electrical Engineering with a minor in Intelligent Systems at UCL from 2016 to 2019. Her education has equipped her with a strong foundation in both machine learning and engineering principles.
Participation in NeurIPS Conference
Chiara Campagnola participated in the NeurIPS conference, which focuses on advancements in artificial intelligence and its applications in various fields, including the physical sciences. Her involvement in such a prestigious event highlights her engagement with the latest research and developments in the machine learning community.